The Basics of LiDAR - Light Detection and Ranging - Remote Sensing

Authors:

Leah A. Wasser

Table of Contents

LiDAR or Light Detection and Ranging is an active remote sensing
system that can be used to measure vegetation height across wide areas. This
page will introduce fundamental LiDAR (or lidar) concepts including:

What LiDAR data are.

The key attributes of LiDAR data.

How LiDAR data are used to measure trees.

The Story of LiDAR

Key Concepts

Why LiDAR

Scientists often need to characterize vegetation over large regions to answer
research questions at the ecosystem or regional scale. Therefore, we need tools
we need tools that can estimate key characteristics over large areas because
we don’t have the resources to measure each and every tree or shrub.

Conventional, on-the-ground methods to measure trees are resource
intensive and limit the amount of vegetation that can be characterized! Source:
National Geographic

Remote sensing means that we aren’t actually physically measuring things with
our hands. We are using sensors which capture information about a landscape and
record things that we can use to estimate conditions and characteristics.
To measure vegetation or other data across large areas, we need remote sensing
methods that can take many measurements quickly, using automated sensors.

LiDAR data collected at the Soaproot Saddle site by the National
Ecological Observatory Network's Airborne Observation Platform (NEON AOP).

LiDAR, or light detection ranging (sometimes also referred to as active laser scanning) is one
remote sensing method that can be used to map structure including vegetation
height, density and other characteristics across a region. LiDAR directly
measures the height and density of vegetation on the ground making it an ideal
tool for scientists studying vegetation over large areas.

How LiDAR Works

How Does LiDAR Work?

LiDAR is an active remote sensing system. An active system means that the
system itself generates energy - in this case, light - to measure things on the
ground. In a LiDAR system, light is emitted from a rapidly firing laser. You can
imagine light quickly strobing from a laser light source. This light travels
to the ground and reflects off of things like buildings and tree branches. The
reflected light energy then returns to the LiDAR sensor where it is recorded.

A LiDAR system measures the time it takes for emitted light to travel to the
ground and back. That time is used to calculate distance traveled. Distance
traveled is then converted to elevation. These measurements are made using the
key components of a lidar system including a GPS that identifies the X,Y,Z
location of the light energy and an Internal Measurement Unit (IMU) that
provides the orientation of the plane in the sky.

How Light Energy Is Used to Measure Trees

Light energy is a collection of photons. As photon that make up light moves
towards the ground, they hit objects such as branches on a tree. Some of the
light reflects off of those objects and returns to the sensor. If the object is
small, and there are gaps surrounding it that allow light to pass through, some
light continues down towards the ground. Because some photons reflect off of
things like branches but others continue down towards the ground, multiple
reflections may be recorded from one pulse of light.

LiDAR waveforms

The distribution of energy that returns to the sensor creates what we call a
waveform. The amount of energy that returned to the LiDAR sensor is known as
"intensity". The areas where more photons or more light energy returns to the
sensor create peaks in the distribution of energy. Theses peaks in the waveform
often represent objects on the ground like - a branch, a group of leaves or a
building.

An example LiDAR waveform returned from two trees and the ground.
Source: NEON .

How Scientists Use LiDAR Data

There are many different uses for LiDAR data.

LiDAR data classically have been used to derive high resolution elevation data

LiDAR data have historically been used to generate high
resolution elevation datasets. Source: National Ecological Observatory
Network .

LiDAR data have also been used to derive information about vegetation
structure including

Canopy Height

Canopy Cover

Leaf Area Index

Vertical Forest Structure

Species identification (if a less dense forests with high point density LiDAR)

Discrete vs. Full Waveform LiDAR

A waveform or distribution of light energy is what returns to the LiDAR sensor.
However, this return may be recorded in two different ways.

A Discrete Return LiDAR System records individual (discrete) points for
the peaks in the waveform curve. Discrete return LiDAR systems identify peaks
and record a point at each peak location in the waveform curve. These discrete
or individual points are called returns. A discrete system may record 1-4 (and
sometimes more) returns from each laser pulse.

A Full Waveform LiDAR System records a distribution of returned light
energy. Full waveform LiDAR data are thus more complex to process however they
can often capture more information compared to discrete return LiDAR systems.

LiDAR File Formats

Whether it is collected as discrete points or full waveform, most often LiDAR
data are available as discrete points. A collection of discrete return LiDAR
points is known as a LiDAR point cloud.

The commonly used file format to store LIDAR point cloud data is called .las
which is a format supported by the Americal Society of Photogrammetry and Remote
Sensing (ASPRS). Recently, the .laz
format has been developed by Martin Isenberg of LasTools. The differences is that .laz is a
highly compressed version of .las.

Data products derived from LiDAR point cloud data are often raster files that
may be in GeoTIFF (.tif) formats.

LiDAR Data Attributes: X, Y, Z, Intensity and Classification

LiDAR data attributes can vary, depending upon how the data were collected and
processed. You can determine what attributes are available for each lidar point
by looking at the metadata. All lidar data points will have an associated X,Y
location and Z (elevation) values. Most lidar data points will have an intensity
value, representing the amount of light energy recorded by the sensor.

Some LiDAR data will also be "classified" -- not top secret, but with specifications
about what the data are. Classification of LiDAR point clouds is an additional
processing step. Classification simply represents the type of object that the
laser return reflected off of. So if the light energy reflected off of a tree,
it might be classified as "vegetation". And if it reflected off of the ground,
it might be classified as "ground".

Some LiDAR products will be classified as "ground/non-ground". Some datasets
will be further processed to determine which points reflected off of buildings
and other infrastructure. Some LiDAR data will be classified according to the
vegetation type.